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Record W1976130679 · doi:10.1121/1.1314317

The effect of moisture on compressional and shear wave speeds in unconsolidated granular material

2000· article· en· W1976130679 on OpenAlexaboutno aff
F. Douglas Shields, James M. Sabatier, Mark Wang

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsnot available
FundersU.S. Department of Agriculture
KeywordsMaterials scienceWater vaporVapour pressure of waterVapor pressureComposite materialMoistureMineralogySPHERESSoda-lime glassThermodynamicsChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The effect of water vapor on the shear and compressional wave speeds in two different kinds of glass beads and in Ottawa sand has been measured. The nominal diameter of the glass beads was 125 microm and of the sand, 500 microm. Measurements were made as the water vapor was introduced slowly into the evacuated material. The vapor pressure isotherm for the beads made of glass with a high concentration of titanium and barium oxides was fit reasonably well by the simple Brunauer-Emmett-Teller (BET) theory. For the Ottawa sand, the BET theory fit the vapor pressure isotherm if the surface area of the grains was assumed to be three times the area calculated, assuming all of the grains were spheres with a diameter of 500 microm. In these two materials, the vapor had little effect on the wave speeds. For beads made of glass containing sodium oxide, however, the wave speeds approximately double with the introduction of water vapor, and the vapor pressure isotherm had the BET shape only if the saturated vapor pressure was assumed to be lowered by 20%. These results have been explained by assuming that a chemical reaction occurred between the lime glass and the water to form a gel.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.207
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicSeismic Waves and AnalysisFrench-language works237,207